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Overview of INEX Tweet Contextualization 2014 track

Proceedings article published in 2014 by Patrice Bellot ORCID, Véronique Moriceau, Josiane Mothe, Eric Sanjuan, Xavier Tannier
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Question mark in circle
Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

140 characters long messages are rarely self-content. The Tweet Contextualization aims at providing automatically information - a summary that explains the tweet. This requires combining multiple types of processing from information retrieval to multi-document sum- marization including entity linking. Running since 2010, the task in 2014 was a slight variant of previous ones considering more complex queries from RepLab 2013. Given a tweet and a related entity, systems had to provide some context about the subject of the tweet from the perspective of the entity, in order to help the reader to understand it.